Kaniappan Vivekanandan and Duraisamy Ramyachitra
Bacterial foraging, ant colony optimization, artificial bee colony algorithm, genetic algorithm, scheduling, grid
Computational grid is heterogeneous in nature as the resources are geographically dispersed throughout the world and hence scheduling the tasks to the resources is a major issue of concern. There are many scheduling algorithms in the literature and the main focus of these algorithms is to reduce the starvation of the resources. This paper proposes the use of bacterial foraging optimization algorithm and its hybrids for task scheduling. This has resulted in higher reduction in the makespan for the proposed method compared to existing scheduling heuristics such as OLB, MET, MCT, Min-min, Max-min, genetic algorithm, ant colony optimization and artificial bee colony algorithms. The utilization of the resources is also high for the proposed method compared to the existing ones. In addition, the parameters such as number of bacteria, chemotactic steps and swim length have a significant impact on the makespan for the proposed techniques. The efficient value for these parameters has been found out using the simulation results and is given.
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